Archives: Hedge Funds
Demand Signals: What to Crawl to Measure Real-Time Demand
January 23, 2026 | By David Selden-TreimanReal-time demand shows up on the web before it hits earnings. Track search, inventory, delivery shifts, pricing, marketplace ranks, and reviews to spot inflections early, then convert them into backtest-ready time-series signals.
Event-Driven Hedge Fund Strategies Powered by Web Crawlers
January 22, 2026 | By David Selden-TreimanTurn the public web into an early-warning catalyst system. Potent Pages builds bespoke web crawlers that detect market-moving events early, structure signals for backtests, and deliver alerts or APIs your fund controls.
Macro Signals Generated from Web-Scraped Data
January 21, 2026 | By David Selden-TreimanMacro signals don’t have to wait for lagged releases. Learn how web-scraped data, prices, inventory, hiring, delivery times, and corporate updates, can be engineered into durable, backtest-ready indicators your fund controls.
When Web Data Is Directional vs Predictive
January 20, 2026 | By David Selden-TreimanNot all web data is predictive alpha. Some signals are directional, useful for context, confirmation, and risk overlays. Others can be engineered into stable, backtest-ready features with measurable lift. Know which is which.
Web Crawlers for Long/Short Equity Hedge Funds
January 19, 2026 | By David Selden-TreimanCustom web crawlers give long/short equity funds earlier signals from the public web, pricing, inventory, sentiment, hiring, and competitor moves, delivered as clean, backtest-ready time-series data you fully control.
Separating Noise from Signal in Large-Scale Web Data
January 18, 2026 | By David Selden-TreimanTurn web-scale crawling into investable alternative data. Learn how hedge funds separate signal from noise using bespoke pipelines: deduping, change detection, normalization, and monitoring for durable, backtest-ready time-series outputs.
Feature Engineering for Web-Scraped Financial Signals
January 17, 2026 | By David Selden-TreimanTurn messy web data into investable signals. Learn how hedge funds use feature engineering to normalize pricing, inventory, hiring, and narrative data into point-in-time, backtest-ready indicators with monitoring and drift detection.
Cleaning, Normalizing, and Structuring Web Data for Investment Use
January 16, 2026 | By David Selden-TreimanScraping is easy. Making web data investable is the hard part. Learn how cleaning, normalization, and structuring turn noisy pages into stable, backtest-ready time series hedge funds can trust and deploy.
From Raw Web Data to Tradable Signals: A Hedge Fund Workflow
January 15, 2026 | By David Selden-TreimanTurn messy public web activity into reliable, backtest-ready signals. This guide walks hedge funds through acquisition, normalization, feature engineering, validation, and monitored live delivery with bespoke data pipelines.
Testing Investment Hypotheses with Custom Web Data
January 14, 2026 | By David Selden-TreimanTurn investment theses into measurable signals. Potent Pages builds custom web crawlers that capture pricing, inventory, hiring, and sentiment changes over time, delivering backtest-ready datasets so your fund can validate faster and act earlier.